Cortical feedback alters visual response properties of dLGN relay cells (Martínez-Cañada et al 2018)

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Accession:239878
Network model that includes biophysically detailed, single-compartment and multicompartment neuron models of relay-cells and interneurons in the dLGN and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed (‘push-pull’) and phase-matched (‘push-push’), as well as different spatial extents of the corticothalamic projection pattern. This project is the result of a research work and its associated publication is: (Martínez-Cañada et al 2018). Installation instructions as well as the latest version can be found in the Github repository: https://github.com/CINPLA/biophysical_thalamocortical_system
Reference:
1 . Martínez-Cañada P, Mobarhan MH, Halnes G, Fyhn M, Morillas C, Pelayo F, Einevoll GT (2018) Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells. PLoS Comput Biol 14:e1005930 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Thalamus;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: LFPy; NEURON; NEST; Python;
Model Concept(s): Vision;
Implementer(s): Martínez-Cañada, Pablo [pablomc at ugr.es];
TITLE High threshold calcium current
:
:   Ca++ current, L type channels, responsible for calcium spikes
:   Differential equations
:
:   Model of Huguenard & McCormick, J Neurophysiol, 1992
:   Formalism of Goldman-Hodgkin-Katz
:
:   Kinetic functions were fitted from data of hippocampal pyr cells
:   (Kay & Wong, J. Physiol. 392: 603, 1987)
:
:   Written by Alain Destexhe, Salk Institute, Sept 18, 1992
:   Modified by Zhu et al, 1999: Neuroscience 91, 1445-1460 (1999).
:   Modified by Geir Halnes, Norwegian University of Life Sciences, June 2011


INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
THREADSAFE
	SUFFIX ical
	USEION Ca READ Cai, Cao WRITE iCa VALENCE 2
      RANGE pcabar, g
	GLOBAL 	m_inf, taum, sh1, sh2
}


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(molar) = (1/liter)
	(mM) = (millimolar)
	FARADAY = (faraday) (coulomb)
	R = (k-mole) (joule/degC)
}


PARAMETER {
	v		(mV)
	celsius	= 36	(degC)
	eCa     = 120		(mV)
	Cai 	= .00005	(mM)	: initial [Ca]i = 50 nM
	Cao 	= 2		(mM)	: [Ca]o = 2 mM
	pcabar	= 9e-4	(mho/cm2)
	sh1 	= -17		 : Modified (-10 in Zhu et al. 99a)
	sh2	= -7		 : Modified (0 in Zhu et al. 99a)
}


STATE {
	m
}

INITIAL {
	tadj = 3 ^ ((celsius-21.0)/10)
	evaluate_fct(v)
	m = m_inf
}


ASSIGNED {
	iCa	(mA/cm2)
	g       (mho/cm2)
	m_inf
	taum	(ms)
      tadj
}

BREAKPOINT { 
	SOLVE states METHOD cnexp
	g = pcabar * m * m
	iCa = g * ghk(v, Cai, Cao)
}

DERIVATIVE states { 
	evaluate_fct(v)
	m' = (m_inf - m) / taum
}


UNITSOFF
PROCEDURE evaluate_fct(v(mV)) {  LOCAL a,b
:  activation kinetics of Kay-Wong were at 20-22 deg. C
:  transformation to 36 deg assuming Q10=3

	a = 1.6 / (1 + exp(-0.072*(v+sh1+5)) )
	b = 0.02 * (v+sh2-1.31) / ( exp((v+sh2-1.31)/5.36) - 1)
	taum = 1.0 / (a + b) / tadj
	m_inf = a / (a + b)
}

FUNCTION ghk(v(mV), ci(mM), co(mM)) (.001 coul/cm3) {
	LOCAL z, eci, eco
	z = (1e-3)*2*FARADAY*v/(R*(celsius+273.15))
	eco = co*efun(z)
	eci = ci*efun(-z)
	:high co charge moves inward
	:negative potential charge moves inward
	ghk = (.001)*2*FARADAY*(eci - eco)
}

FUNCTION efun(z) {
	if (fabs(z) < 1e-4) {
		efun = 1 - z/2
	}else{
		efun = z/(exp(z) - 1)
	}
}
UNITSON

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